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Record W2017645377 · doi:10.1039/c2em10366d

Propanil in a Manitoba soil: an interactive spreadsheet model based on conventional chemical kinetics

2012· article· en· W2017645377 on OpenAlexaffabout
Donald S. Gamble, G. R. Barrie Webster, Marc Lamoureux

Bibliographic record

VenueJournal of Environmental Monitoring · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicPesticide and Herbicide Environmental Studies
Canadian institutionsUniversity of ManitobaSaint Mary's University
FundersEuropean Food Safety Authority
KeywordsSorptionChemistryKineticsDiffusionDesorptionPropanilChemical kineticsEnvironmental chemistryVadose zoneSoil waterChemical engineeringThermodynamicsSoil scienceEnvironmental scienceOrganic chemistryAdsorptionPesticide

Abstract

fetched live from OpenAlex

An interactive spreadsheet model has been created for quantitative predictions of propanil sorption and reaction in a slurried Manitoba clay soil. Based on experimental values for the numbers of empty and filled sorption sites as reactants and products, the reaction mechanism has been described with conventional chemical kinetics. The on line HPLC μ extraction method revealed labile sorption, intraparticle diffusion, and a chemical reaction. Laidler's integral rate law for second order kinetics describes the labile sorption. Desorption, intraparticle diffusion, and the chemical reaction are all described by first order kinetics. The time dependent effects of initial concentration and amount of slurried soil can be predicted for sorption, intraparticle diffusion, and the amount of reaction product. Suggested applications include storm runoff and inputs for fate and transport hydrology models.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.956
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.250
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2012
Admission routes2
Has abstractyes

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